More Pipeline, Less Revenue

0:00 Guy Rubin is the founder and former CEO of Epsta, the revenue intelligence platform he built over more than a decade to help B2B sales teams stop guessing and start measuring what actually drives deals. Relationship strength, pipeline health, and deal momentum. In 2025, Epsta was acquired by Fullcast, and Guy now serves as Managing Director of Revenue Intelligence, where he's helping build out what they call a full revenue orchestration engine, connecting GTM planning, territory design, and sales execution into one system. Guy is also highly involved with Pavilion, one of the largest executive communities in the Saas world, and

0:43 he's the mind behind the report we're going to dig into today. The 2026 revenue orchestration benchmark report. This thing analyzed over 360,000 opportunities worth $78 billion, and the findings are pretty staggering. A 28% collapse in sales efficiency, an 87% gap between companies that used AI for precision versus volume, and the fact that 50% of sellers still missed 80% of their quota this year. We're going to dive into everything the benchmark report reveals and how top performing sales orgs are operating in the world of AI. Guy, you've been running this report for a few years. What's the most shocking thing in this year's edition?

1:32 Well, Anthony, first of all, thank you so much for having me. I remember last year we did it in person. I think we were in San Francisco when we did the review of the '25 report, so I always look forward to our sessions together. Yeah, it's been an interesting year for those in Saas. I think that's probably an understatement. The number of things that really hit me that were really shocking in the report. I mean, if we start at the very top, we saw that quotas actually came down for most sellers in 2026. Even with a reduction in quota requirements, the number of sellers that missed quota was over three quarters. As you said earlier,

2:05 over 50% of sellers actually missed 18% of their number. That in itself is just massively unsustainable. The delta between what top performers are achieving and the rest of our sales team has got even wider this year. Those are the most shocking headlines, I suppose, from my perspective. But when we go one layer down, what really hits me is that the money spent on AI in 2025 and moving into 2026 now is huge. Everyone's investing in it in their go-to-market motion. But with all of that investment in AI, we'd expect sales efficiency to move up and to the right. But in fact, we saw it drop last year. That to me is the

2:45 most concerning data point out of all of them. 100% agree these teams are spending insane amounts of money on scaling out their sales teams and investing heavily into these AI systems, AI-powered services. To hear that half of the teams aren't even achieving the 80% mark after having a lowered quota, it's just what's broken, what's going wrong here? Well, what we're starting to see is an emergence of two AI strategies or two AI worlds, from what I can tell. To answer your question, the single biggest problem we're seeing is that if you've got a broken go-to-market motion, if you don't know what your ICP is, if there's

3:27 no rigor or discipline in qualifying opportunities out, if you're not consistently multi-threading, if you don't have proper entry and exit criteria for the stages that you're working through in your sales process, when you put AI on top of your existing go-to-market motion, what it does is it exacerbates the problems that you've already got. For example, if we think about top of funnel, effectively, you can generate infinite number of leads now using AI. The problem is that if you haven't defined what ICP looks like and you understand how to qualify out, you end up with huge volumes of opportunities

4:03 that aren't real. We've seen sales organizations having to scale their sales teams up just because of the volume of opportunities that are coming in top of funnel, when in fact the volume that actually match ICP has actually diminished, not gone up. All of that compounds these inefficiencies that we're seeing when you've got sellers not picking opportunities based on how well they fit the business that they're trying to sell. In fact, just starting with the A's and then going to the B's and so on. There's all sorts of inefficiencies that we've known in go-to-market for a long time. Instead of trying to fix those and getting

4:37 much more aligned and disciplined and using AI to keep everyone focused on best practice. If all you're doing is using AI to generate more volume, all you're going to do is cause yourself a whole lot more set of problems and we see a sales efficiency or revenue per seller actually drop by 25% within those organizations. Even though the volume of deals that they worked on went up by, get this 68%, 68% more volume in a single year and in the same year sales efficiency or revenue per seller dropped by 25% in those organizations across the board. Huge inefficiencies in the way that we're going to run.

5:13 One of my favorite CROs I ever worked with, his name's Tom Miller. I worked with him at emailage and was with him through the exit. He had a saying that I think is really relevant to this. It's a golf metaphor. If you have a bad swing and practice more, your golf game is going to get worse. It's not going to get better with more practice. I think that's what we're seeing here with AI too. If you don't have the fundamentals, if you don't have a good process like you mentioned and then you throw on accelerant into the process, it's even worse. It doesn't help you incrementally improve.

5:47 I think that's exactly right. We've been preaching this for a long time, best practice and trying to deal with this delta between what top performers are achieving consistently and then the rest of our sales teams. The problem is there's been very little capacity for coaching, for sales training. In fact, what tends to happen is a team starts to miss their number and all that coaching goes out the window. We just start working on deal reviews. You end up with this constant granular focus on deal review, deal review, deal review. In fact, what we need is a system that's scalable. We need to be focusing on the right deals

6:23 on the top of funnel. We need to target ICP. ICP is a living breathing entity. We learn new things about customers and prospects every time we interact with them and all of these things contribute to what ICP looks like. Then we need to be funneling the right deals to the right sellers. Not every seller is competent at selling every solution to every buyer. We need to make sure that the right sellers are getting access to the right opportunities. Once they get them and start working with that customer, they need to qualify the customer well. It sounds like basics and these are things that we've known forever, but it matters

6:56 even more today than before because we've got so much more volume to get through. Qualifying out matters so much. In fact, we do these what we call revenue insights as a service. We produce reports for our customers every quarter that's effectively an audit their whole go to market motion. What we see time and again when you're dealing with a company that's got multiple territories, the territory that qualifies out the most in those early discovery stages are the territories that generate the most revenue for the business. That's just one example. Other data points include qualification. It's not a coincidence

7:30 that the top territory is always the territory that has the highest qualification scores. These things ring true not just today, but have run true forever. I'm trying to throw AI and trying to effectively brute force. AI for these businesses has become the new growth at all cost model. In the old days, we just throw lots of money at it. Now we're just throwing lots of AI at it and expecting better results. In fact, what's happening is your sales efficiency is getting lower and we're spinning wheels because we've got so much volume to work through and the sellers are so scared to close anything off as lost

8:09 because they're not hitting their number and they're not getting any coaching because we're not hitting our number so we need to focus on deal reviews rather than coaching and it becomes a suspicious cycle. It's not a surprise that when you look at the data as to why these businesses are not performing how they could do. It's really interesting. You would think most companies, more pipeline, every single unit of more pipeline would be better, but actually there's a diminishing return and then an inverse relationship because I'm assuming if you're overloaded with pipeline, you simply don't

8:43 have the time to multi-thread, do a quality process, go deep and wide within an organization of the deals that have the highest propensity to buy. More pipeline isn't always better. I'm interested in hopping into the data and seeing maybe where that balance is. When is pipeline too much pipeline and where should people be looking out for where, hey, what are the signals that maybe you need to rebalance your territories a little bit and focus more on qualification? Well, you'll be pleased to hear in the report there's a whole piece on overloaded pipeline and the impact it has on win rates. When the sellers have too much pipeline, their win

9:25 rates drop dramatically. When they've got a balanced pipeline, the win rates are almost twice as high. You can see the data in the report, but it's not just the win rates. As we go into it in a little bit more detail, sellers with too much pipeline engage with the customers less and they're also multi-threaded less. Of course, guess what? We're not putting the energy into those opportunities and really they're just getting a very high level overview from the seller. The win rates, that's why the win rates are dropping so much. One of the most important things is to make sure you've got balanced territories. That's not

10:03 an easy task, but yeah, you really want to make sure that and you can see it in the data. The territories that have got the right balance with the right number of sellers and the right number of opportunities and the consistent process to manage within there are the territories that are willing to an excess over the rest of the territory teams. Whenever we engage with a client, number one goal, we get their growth model aligned. We need to know, "Hey, how ambitious are you? What growth targets do you need to hit? Let's reverse engineer a plan." Immediately after that, the most important thing for any company,

10:35 we call it market map, which is aligning your ICP, getting balanced territories, understanding which accounts and logos have the highest value for your company if you close them, and then dialing in your messaging, your outbound, your sales process to point every single sales and marketing dollar towards those companies that have the highest propensity to buy so you can be as efficient as possible. Otherwise, you're wasting so many resources and so much sales and marketing ammunition on the wrong people. When the world is as noisy as it is today, you really, really need to fine tune that aperture.

11:14 I think your point is spot on. When we look at the data, we can see that about 10% of the pipeline really matches ICP on average. Really, you want that to be at about a third. We're spending over 60% of the opportunities that we're working on are what we call oversaturated, where the pipeline has a diminished return. Opportunities in this oversaturated space are either very, very competitive and the win rates tend to be a lot lower or the time to close is so long. You're spot on. We know that the most efficient deals are the ones that close. We see more often than not the largest opportunities are the most efficient deals, the ones that generate

11:58 the most dollars per day. When we look at the pipeline spread, we see that the largest opportunities or the ones that are most efficient tend to represent less than 10% of the pipeline. Then when you overlay that with ICP, and again, trying to define what ICP, a lot of companies are getting confused between ICP and TAM. They think any company that we can sell to, that's our ICP. When in reality, we want to get that segment really as small as we possibly can, something we can get our hands around so that we understand what makes that opportunity ICP. It's not just about industry or market. It could be about where they are in their growth

12:37 cycle. Have they just appointed new board members? Are they about to go through an exit? Have they just done a raise? Have they got a new CEO in place? Are they expanding into a new market? Are they sunsetting an old product? All of these are, and many more signals can influence whether an opportunity falls into or outside of ICP. If we've got the right rigor and the discipline in place and we're curious enough and we're asking the right questions, then opportunities that fit ICP in stage one or two of the sales cycle, it's absolutely legitimate. But by stage three or four, we find out that actually they fall

13:14 on outside of ICP and we probably need to close these deals off as lost. I think you should have your fundraising and your exit ICP and keep those books completely separate from your sales and marketing ICP. Our head of education loves to say the riches are in the niches. So if you can really, really get fine-tuned, like you said, layering in those signals, layering in the exact, the personas too. I think sometimes we think of ICP as what companies we should be targeting, especially B2B. You're like, "Oh, okay. We work with B2B SaaS companies after Series B maybe before Series D." But at the end of

13:53 the day, there's a person who's going to buy and who are those people and they have pains and goals and pressure and things that they're trying to do. How can you get the right companies, the right people, then layer in the right intent signals and timing and just really, really narrow who you're going after? Because there is a group of people to where it should be an absolute no-brainer that they would be buying from you and you should go find those first. Of course, I agree with that. What's really interesting is that the top performers can smell those opportunities. If you've got a broken process and you've got infinite leads

14:30 coming through and you're not dating the sellers, the top performers are the ones that are going through that list and they're picking out the ones that really do match ICP because they know that their time is precious and they're the ones that are ruthless about qualifying out. The very best sellers are qualifying out three quarters of their opportunities by the time they need discovery. Only about 25% of their deals are moving through the process, but what's amazing is if you qualify out three quarters of your opportunities at discovery stage, number one, you free up all your time to work on better opportunities. The magic

15:02 really happens late stage. That work that happened early stage, that qualification that went on, that really kind of understanding that there is a critical event that you're working towards, that we know that there's a budget, that we understand that the decision-makers are and so on. When you look at the later stages, we see very little slippage and almost 100% conversion rates all the way through the different stages. We see that in every time we see a different company with lots of different territories, the territory that's over-performing, they are qualifying out more than anybody else and they see this magic

15:34 late stage where the opportunities whizz through those later stages and the win rates are almost very, very high. Certainly over 70% of the deals that lead to discovery and continue go on to win. That's really special. Why is it that the top performers are able to smell that out? Because they understand what good looks like and they're ruthless in their qualification and the way they run their sales cycle. I'm wondering, those top performers, is it something that can be trained or is it something that you have to have a level of talent for and you need to suss out in the recruiting process? How do we make sure we get more of

16:16 those people in a roster? I think ultimately, we need sellers that are curious. You do need a certain level of caliber of resource to actually be a good seller. I thought this for a long time, that it's not about those heroics anymore. It's not about, "Let's just find those heroes that are going to help us get that number over the line." It's about the system. It's about the process. What we need to do is build as leaders, our responsibility is to give sellers an environment they can win in. How do we do that? Well, what we need to do is show them what good looks like. The beauty of today that we live in, the days

16:56 that we now live in, is that we've got access to all this data. We can process it for pennies. We can give the sellers evidence as to what good looks like based on all of the activity that's gone on in the past. Now, that can be a challenge if you're like every other business in the world. Your sales force data might not be particularly clean, but forecast is a good example of a business that's able to bring together data from mailboxes, from calendars, from call recorders, as well as CRM. We can build those benchmarks really quickly. We can show the sellers in pictures what good looks like at every stage of every

17:32 sales cycle. Then it's up to the leadership team and the RevOps function to keep everyone in line. Actually, the good news is because the sellers are coin-operated, because they are motivated by wanting to win more, once you convince them that you've got the secret source, you know how to help them win more. You know how to help them identify what ICP looks like. You know how to help them qualify out through a course of their opportunities at the discovery stage. You know which stakeholders they need to be multi-threaded with before they leave stage three of the sales cycle. Once you show them in picture forms how to

18:06 win more, how to make more money, the speed in which they want to follow that playbook is incredible. The issue here is a leadership issue. It's our role as leaders to actually show the sellers and give them a guide as to how to win. Because they're coin-operated, they will follow, but they have to believe that what you're giving them is the accurate outcomes. It's our job to give them that right system. I think the toughest part is so many companies are getting to this part too late where they didn't do the work on ICP. They didn't do the work on orchestration. They didn't do

18:41 the work to find out the most efficient path to win a deal. Instead, they hired an army of salespeople. Then you have an army of salespeople in C. Nobody wants to get fired. Now they're keeping their pipeline open. They're spinning their wheels on a bunch of deals that don't make any sense. For a company that's in that really difficult situation, what advice would you give them? How do they turn that ship around when it feels like maybe it's gone too far? That's the question we're answering at the moment. I'm pleased you asked it. The short answer is we need to come in and do this audit so that the data will set us free. Every day

19:23 we hide away from the reality of what good looks like is another day it's going to take us to get to where we need to get to. It doesn't matter how inefficient we are today. What matters is that next quarter we're more efficient. The quarter after that we're more efficient again. That's what RevOps is all about. We need to get the leadership team brought into the principle that we've got some challenges, but there's a root out of this. It's not just throwing more AI tools at the sellers. We need to get under the skin of what good looks like for every different go-to-market motion that we have. We need to really lock down

19:56 what best practice looks like, and we need to understand the gap to good for each of our individual sellers. We've developed this revenue insights as a service report. It's a 50-page audit. Plug and play takes two hours to connect to the platform, and it goes back a year through all the historical deals that close won and lost, and it includes five chapters. Chapter one is just an overview of sales efficiency and whether it's trending up or down. Chapter two is the win-loss analysis. This is big. We go through every deal, close won and close lost, and we're looking at things like how multi-threaded we are. We look at how well

20:29 we qualified. We look at which stakeholders have a positive influence on outcomes, and the list goes on. Once we've done all that win-loss analysis, we can then apply that to the live pipeline and see where the risks are and the deals that are in flight. That's beautiful because it shows them what they can do practically now to have a positive influence. Chapter four is around rep coaching. Where's the gap? We get a lot of that from listening to the core recordings and letting AI tell us where the sellers are doing well and where they need attention. Then chapter five is the sales process itself. Where's the friction

21:00 points that we can start to remove? The beauty of delivering these reports every three months is that we get to sit with the leadership team and understand where their challenges are, and then three months later, we get to see if they've had a positive influence on them and what they need to do next to actually drive efficiency and get the business moving up into the run. That's a fantastic report, by the way, and I think any company that is past a certain scale point would benefit very much from getting access to that data. After you deliver those results, how do you see companies typically

21:31 begin to turn it around? Do they have enough agility to be able to implement those and keep the team? Or do you end up needing to have a right sizing of the team? What tends to be the tactical execution following those reports? Yeah, it really depends on where you are on that maturity curve and what internal resources you've got, because we need some sort of RevOps function to be responsible for change. In some organizations, they've got that internally and they can use these reports to incrementally improve. Other times, they'll bring in external experts like yourselves, and lean scale experience

22:10 doing this stuff and helping those businesses to wade through the challenges and see those incremental improvements really quickly. As I said before, the good news is that once the sellers are on board, they all want to earn more money. Frankly, as you said before, they want to save their jobs, but about 20% of them are never going to make it, and we just need to recognize that. The sooner we can identify that 20% are, the quicker we can move them on. You've got the 20% at the top that are just firing at all cylinders and overachieving their targets, but it's the middle lot that we need to really decide

22:45 whether there's an opportunity to actually move them up and to the right. More often than not, the things that we identify are relatively quick to change, but it's about introducing that rigor. We need entry and exit criteria for the different stages in your sales process, and we need to stick to them. We need to know that if we don't get engaged with the ... When the data tells us that our win rates are four times higher if we engage with the finance persona at stage two instead of stage five, well, guess what? You don't get to leave stage two if we don't have engagement with the finance persona,

23:17 and that's a real challenge because you have to have a difficult conversation with your buyer and say, "Look, I'm here to help you. Let's say you're buying HR software." Well, you might buy HR software twice in your life, right? Well, I sell it all day long. I don't, but I sell of mine. I'm here to help you buy this, and I know what the gotchas are going to be, so let me help you and advise you through this process, and I want to give you access to all the solution engineers you need and all the collateral that you want, but if you can't give me access to the right resources, then now's not the right time for you to buy

23:50 this software, and let's push this off. We'll do it in six months' time, and all of a sudden, you'll know that expert advisor that helped them to avoid a mistake they were about to make, and you're the person they're going to come back to. I think our role in selling is to ultimately help the buyers to buy, and I think more often than not, they want to be guided as to what does best practice look like. How do we do this properly, and not just through stages and find ourselves in a place where perhaps we've all wasted a lot of time and energy? It only takes a couple percentage point improvements on conversion rate and a slight improvement

24:27 on deal velocity to really, really start moving the needle on the efficiency metric. I think, as you're mentioning, hey, can we upskill that middle? Of course, there's people you might have to make some hard decisions with, but that middle, if we can get a few more percentage points of higher conversion, reduce sales cycle by a few weeks, you could really start to see that velocity go. One stat in the report that I thought was really, really interesting, and I was hoping you could maybe peel back the layer of the onion as to why this is the case. I know a lot of companies that we're working with are doing everything they can to move up market.

25:08 There's a lot of intuition as to why you should do that, and higher LTV and everything, but I thought this was really interesting that larger deals are over six times more efficient than smaller deals. Love to hear why. Well, I think the reality is that while larger deals do take longer to close, as a proportion, they don't take anywhere near as long. If you take it down to dollars per day, you generate from those opportunities. That's the data point we lean into. When we talk about sales efficiency, we're effectively talking about dollars per day. Yes, in general, the larger

25:44 deals ... First of all, the businesses that haven't gone brute force, that haven't gone growth at all cost, just throw infinite AI at top of funnel. Those that are using AI to introduce that structure, to get everyone working best practice. We actually saw the number of deals they closed in the year just dropped slightly. Not huge, but just slightly, but the revenue per seller jumped dramatically, because exactly as you say, they moved up market. Their average deal size went up dramatically. They moved up market to larger opportunities, much more focused on ICP. That structure, that rigor, meant that they were qualifying

26:21 out deals that didn't match quickly, and focusing their energies on the deals that mattered. We saw the sales efficiency go through the roof in those organizations. It's not a surprise that the bigger deals generate more revenue, but it's worth understanding it's not just more revenue that they generate. They're more efficient as deals on their own. The opportunity for cross-sell up-sell down the line is much, much greater in those larger opportunities. Actually it's another example of why a CRO is so important to go to market now, because we need to be thinking about not just getting the deals signed, but we need to be signing

26:56 the right deals that have got those expansion opportunities. For what it's worth, we saw 52% of new revenue last year. It didn't come from new logos. It came from expansion in existing accounts. Most businesses we walk into, we find are leaving money on the table with existing customers. In fact, the win rates are nearly twice as high. If you open up a sales opportunity with an existing customer, you've got an average win rate of 45% on those deals, and they close in half the amount of time. It really matters. Again, it's a great example where organizations are leaving money on the table, because they're not really investing

27:39 in that expansion motion as much as they are in the new business and new logo motion. I don't think it was surprising that the upmarket deals are more efficient, just at how much more efficient they are. Six times more efficient if you're in that 70K ACV plus range. I think that's where people have an intuition like, "Okay, I know it's going to be more efficient. I know LTV is better," but the magnitude at how much more valuable those deals are, and then layering on bigger expansion opportunities. If you're launching or releasing new products, you already have additional enterprise deals sitting at your doorstep, stickier, longer

28:22 LTV. Any advice for companies that are trying to move upmarket, maybe they're mid-market, SMB range, and they're trying to get those enterprise deals, what have you seen teams do that has helped successfully move upmarket with their solution? Again, the data will give you the answers. Normally, the buying committee is larger, so we've got more stakeholders to manage. We need to understand, and this is another example of why it's so important to have that structure and rigor around sales process, and the exit criteria, because we could be running an enterprise deal, could take nine

28:58 months to close. We need to be managing every stage of that sales cycle correctly, engaging with the right stakeholders. Different stakeholders have different requirements. A seller wants a product that works really well. The finance persona wants to see a return on investment. The marketing team might have a very different set of agendas to why they're spending the money. There's lots of different stakeholders with lots of different agendas, and we need to understand what their drivers are, and you need to be running a very structured sales cycle with those types of businesses. Reference sites are really powerful as well. It all

29:32 becomes self-fulfilling. What shocks me is that we see so little top of funnel activity going on with those enterprise opportunities, when in fact, that's where the energy needs to be spent, because that's where the real value is. Again, it's that example of, "Well, we haven't got time to work on those enterprise deals, because look at all this volume we've got coming through with our AI top of funnel engine." But it's all crap and low conversion rates with high churn levels and long sales cycles, and we don't want any of that. We need to be a lot more strict about what good looks like. Again, unsurprisingly, with those

30:10 enterprise deals, relationships still drive revenue. It's still vitally important that we're turning up at those events, that we're having those opportunities to build those relationships with those key stakeholders so that we're able to manage those, get into those larger opportunities as we go. Yeah, I think there's a lot of content and garbage out about how AI is going to take over sales, and we're not going to need sellers in the future. I think that's absolutely crazy. If you think about, one of the stats I think is really powerful from the report is deals with six plus stakeholders when at almost 4x the rate. That is a large group of people

30:53 with competing priorities and personalities and things to manage and orchestrate and then navigate all of their attention towards getting a deal done. The part that I find even more shocking is that those buying committees are continuing to grow. The sales process is going to get even more complex in the future. Now, imagine you're a seller and you've got three of those that you're managing. That's doable. I can see that. Now, I'll throw on top of another 100 SMB deals that are going to spend 10 grand with you, and they're distracting you every five minutes. They've got no internal

31:26 resources, so they're really needy. They're taking up loads of your energy and loads of your time. Now, how much energy are you going to put into those three enterprise deals? You're inevitably going to get distracted, and that's what we see time and time again. We need to recognize that our seller's most precious asset is their time. We need to help as leaders. Our job needs to be to protect their time and have them focusing their energies on the things that are going to generate them the most outcomes and the most revenue. With all of these new paradigms, having AI capabilities, you can really crank up the

32:01 volume if you want to. Using those AI capabilities to really fine tune your ICP, your personas, and really help throughout the qualification process. Knowing that sales processes are getting more complex, but we also have these tools that enable us to be more efficient. Are you seeing any changes in go-to-market org structure? Is the typical B2B SaaS playbook of how to build a go-to-market team changing with all of the new capabilities? Yeah, I think so. I think it's been a long time coming. We're seeing really the top performers are really taking a 360 role. They're not necessarily responsible for all of their own

32:48 top performer activity, but they certainly at the top performers generate nearly three times more of their own opportunities than the average sellers. The same applies once the deal's signed. Again, logic tells us that if we spent six months building a relationship with someone to the point where they trust us enough to sign a contract, it would be crazy to step back from that relationship and let somebody else take over. I think we're seeing sellers take with this 360 role. They're able to land and expand on opportunities, especially in an AI world where we're seeing pricing move to much more consumption-based

33:22 models now. There's steps before we get to true consumption-based, but there's still a motion to effectively align value to what we charge. What matters is that the sellers don't necessarily own the account and run every implementation meeting and activation and onboarding and so on, but they still need to be an absolute point of contact on the commercial side of the opportunity. The beauty of that is that the sellers don't feel that desire or drive to have to win every part of the deal in the first contract. They can just get the deal over the line and then, "Right, we've got our first agent in there.

33:58 It's adding value. We've got three more agents we want to get you up online with." As they start to deliver value, we now start to charge you a bit more money or whatever your model happens to be. I think the role of the seller is to continue to support the buyers and not just, A, talk a funnel to help build those relationships so that when the customer is ready to buy, you're the person they come to. To manage that sales cycle to a place where they trust you well enough to sign the damn contract and then wants the deal signed to continue to nurture the account so that you get that opportunity to cross-sell and

34:35 expand the account as you move forward. I think that this is the new enterprise sales motion that I'm seeing. I'm not sure how new it really is because, ultimately, I grew up in a world where relationships have always driven revenue. I think the idea of these single-purpose vehicles that will just take a seller from stage 1A to 1B and then somebody else picks it up from 1B to 1C and then from stage 2 to 3, someone else picks it up. I think that's behind us now. I think the buyers are educating themselves more and if they aren't going to engage with a seller, they want to trust and advise them now more than ever before.

35:11 Yeah, I've always been a fan of the full-stack AE, the one who can build pipeline, close their own deals, nurture and expand. I think, to your point, it's because you have that thread of relationship. One thing that AI cannot do, AI can't be accountable for the deal going well. When you're selling that HR software and you're making a lot of promises during that deal and you just completely disappear, keeping that thread of accountability and doing what's right, maybe you have to convince the product team to build a new feature in order to justify the deal. Maybe you have to offer certain discounts or do something

35:46 to help enablement, but AI cannot be accountable and be a change agent internally to help drive and be your advocate. That's really where I think the sales job is being in alliance with the prospect of the customer and doing everything you can to win the deal within reason. That's something that AI is never going to be able to do. Yeah, I agree with that, but it can enhance what we do. When we talk to a customer and within two hours, they connect everything to our platform, our AI engine is processing through thousands of hours of call recordings to understand how well do we deal with objections

36:29 and is Celarex getting better at objection handling quarter on quarter or getting worse? Where do they need training? How well are they dealing with qualification? It turns out they're really good at the med, but really bad at the peak or whatever it happens to be. The AI can help us understand where the limitations are or where they need training. Without a doubt, it's there to facilitate and can help us to achieve our outcomes, but it's our role as leaders to put the structure in place and to glean from the AI the information we need to help make the sellers more productive. I think that the lens to always look through

37:05 is that that sells efficiency data point. Maybe if you don't have that data point, coverage is a great one. You want to see the level of coverage each seller needs to hit quote and drop quarter over quarter because they're getting incrementally better. This stuff doesn't just impact revenue, it also impacts growth and ultimately valuation. There's a reason why private equity is jumping on top of these reports we talked about because suddenly all of these private equity organizations have got assets that are underperforming and ultimately that's having an impact on valuation. If they can get under the skin of where that problem

37:42 is and have an incremental improvement, as you were talking about earlier, if you just improved one thing, fine, it may not have a massive impact, but if we can improve the way the ICP targets by 10% and if we can qualify 10% better and if we can be 10% more multi-threaded, you can see where this is going. You start to have a compounding effect and the impact on the outcome at the end of the quarter is material. The next quarter we build on that again and all of a sudden three or four quarters in, we are achieving worldly different results to where we started and I think that's the point here. This stuff isn't just a nice to

38:19 have that might move the needle by a few percentage points. If you get this right, this can transform the whole growth of market motion and impact on valuation can be really material and for the want of the cost of a few RevOps resources or a bit of AI and technology to understand where the challenges are and then influencing that change, you can spend 50, 100 grand and see tens of millions in return if you get this stuff right. It should be no-brainer. I've absolutely seen it in my experience. The company is that, one, you can prove that you can affect the process and the results and you can incrementally improve so you can

39:02 bake that improvement expectation into your valuation. Also, when you have the right data, you have a tight ICP and persona, the way you articulate your growth story during a fundraiser during an exit is night and day if you didn't have this level of organization and that polish, as you mentioned, could mean tens of millions of dollars. Yeah, absolutely and it doesn't take long. We're talking about two or three quarters to start to see the impact. Most of that is down as a credit to the sellers themselves. Once the sellers understand that once you take away all the noise and you make it super

39:37 easy for them to win, if you've got the right curious sellers, you'll start to see the numbers move up to the right really quickly and we've got many, many examples of that and that's why PE is investing in this type of engine because understanding what's going on within the go-to-market motion gives them the baseline to work from and they can start to incrementally approve as they go and as well as ITP, you don't spend money on things that don't have an impact and at least if they do, they turn it off pretty quickly and we're seeing this thing scale pretty fast.

40:05 Guy, I absolutely love this report and I think a lot of the trends that we're seeing are continuing to compound with higher adoption of AI like you mentioned and I think just to recap, some of the most important things, ICP, persona, qualification, it's everything. We have plenty of volume. Let's get focused on the deals that have the highest propensity to buy and it will show up in your sales efficiency through higher conversion, quicker sales cycles, and higher lifetime value. The other thing that I think is interesting is the complexity of deals continuing to grow

40:44 especially if you're moving up market where you're going to get a 6x efficiency over smaller deals then you have to expect that those buying committees are going to get larger and larger. The ones that have 6+ members in that committee or 6+ members that you're multi-threading with tend to close at a much, much higher clip so knowing, hey, you need to have care and attention to these deals, it's going to take time. You need to have the right sellers and seat and if you can improve those metrics across the board and lift up that middle to be more like the top performers, it's going to show up.

41:19 I'm really excited, we'll make sure we share the link to the full report in the YouTube video. We'll share it on LinkedIn as well and I just want to kick it to you. Best way to get in touch with you, the full cast team and then when can we expect the next report because I'm anxious for the results. Thank you, Anthony. Yes. Anyone who wants to get in contact with me, you can do that via LinkedIn and if you mention the podcast, I'll accept the invite 100%, always happy to debate sales and data with anyone. If you're an enthusiast, follow me, I post every day, at least I have done so far in 2026. Let's hope I can keep it going.

41:56 We'll include a link to the live report, it's the largest report we've ever done. We have an H1 update planned for September but rumor has it, we might be launching a missing chapter in the next couple of months so watch this space. All right. I'm excited. I'm excited. The podcast has fueled so many decisions we've made, decisions companies that we're working with make so I really, really appreciate the rich data that you share with the community. It's an amazing report and I just really, really commend you on the efforts. Guy, always a pleasure to have you on the podcast. Thank you again.

42:31 I can't wait to review the next one and see where the numbers are trending and can't wait for our audience to get their hands on the report. Very good. Thanks again everybody and looking forward to connecting with you all.